AWS AI Engineering — From Cloud Beginner to Enterprise GenAI Architect

🚀 A 12-Session Hands-On Journey from AWS Fundamentals to Production-Grade GenAI

Want to move beyond learning individual AWS services and learn how to design, build, deploy and operate real-world AI solutions on AWS?

This structured 12-session program takes you from AWS and AI fundamentals to advanced GenAI, Agentic AI, MLOps, LLMOps and Enterprise AI Architecture.

You will learn through practical examples, AWS architecture patterns, hands-on demonstrations and real-world use cases — with each session building toward an end-to-end production-grade AI solution.

🎯 What You Will Learn

☁️ AWS Foundations for AI & GenAI

Understand the AWS ecosystem, core services, IAM, compute, storage, networking and how AI workloads are architected on AWS.

🤖 Generative AI & Amazon Bedrock

Understand Foundation Models, LLMs, prompting, inference and learn how to build GenAI applications using Amazon Bedrock.

📚 RAG & Enterprise Knowledge Bases

Learn embeddings, vector search, document processing, retrieval and how to build enterprise-grade RAG applications.

🕵️ AI Agents & Autonomous Workflows

Learn agent architecture, tool calling, orchestration, memory and autonomous AI workflows.

🔗 Multi-Agent AI Systems

Design supervisor/worker architectures and build systems where multiple specialized agents collaborate to solve complex problems.

⚙️ MLOps with Amazon SageMaker

Understand the complete ML lifecycle — experimentation, training, pipelines, model registry, deployment and monitoring.

🚀 LLMOps & Production GenAI

Learn how to deploy, monitor, evaluate, version and continuously improve LLM-powered applications in production.

📊 LLM Evaluation & Observability

Understand how to measure quality, detect hallucinations and monitor AI applications using practical evaluation strategies.

🔐 AI Security & Responsible AI

Explore IAM, data protection, Guardrails, prompt injection, security controls and responsible AI practices.

🏢 Enterprise AI Architecture

Learn how to architect scalable, secure, highly available and cost-efficient AI platforms on AWS.

🛠️ What You Will Build

By the end of the program, you will have designed and worked through an enterprise-grade Agentic AI platform combining:

Amazon Bedrock + RAG + AI Agents + AWS Services + MLOps + LLMOps + Security + Observability

The focus is not just on "how AWS services work" — but on when to use them, how to architect them together, and how to take AI solutions from prototype to production.

👥 Who Should Enroll?

This program is ideal for:

• AWS / Cloud Engineers looking to move into AI
• Software Developers interested in GenAI
• AI/ML Engineers
• DevOps / MLOps Engineers
• Solution & Cloud Architects
• Data Scientists
• Technology professionals transitioning into GenAI
• Professionals preparing for enterprise AI architecture roles
• Anyone who wants practical, real-world exposure to GenAI on AWS

📈 Your Learning Journey

Level 1 — Foundation

AWS → AI/ML Ecosystem → GenAI Fundamentals

Level 2 — Builder

Bedrock → RAG → AI Agents

Level 3 — AI Engineer

Multi-Agent Systems → LLMOps → MLOps → Evaluation & Security

Level 4 — AI Architect

Enterprise Architecture → End-to-End Capstone

⭐ Why Join?

This is designed as a practical AI engineering journey, not a traditional AWS theory course.

You will learn to think like an AI Engineer and Architect — starting with a business problem, selecting the right architecture, choosing the appropriate AWS services, building the solution and understanding how to operate it at scale.

12 sessions. One structured journey. From AWS beginner to Enterprise GenAI Architect.